Method and system for providing resiliency in interaction servicing across data centers

ABSTRACT

A system and a method for providing resiliency in a telephony communication system are provided. The method includes: obtaining resources that are available in a first data center; receiving, from a client, a request for accessing a first resource; transmitting, to the client, a first Uniform Resource Locator (URL) that includes information for facilitating a client access to the first resource in the first data center; when the first resource becomes unavailable in the first data center and available in a second data center, transmitting, to the second data center, a subscribe message for facilitating a client access to the first resource in the second data center; and when the client access to the first resource in the second data center is available, transmitting, to the client, a second URL that includes information for facilitating the client access to the first resource in the second data center.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication Ser. No. 63/036,752, filed Jun. 9, 2020, which is herebyincorporated by reference in its entirety.

This application is being filed concurrently on Nov. 4, 2020 with eachof U.S. patent application Ser. No. 17/089,275, entitled “Method andSystem for Interaction Servicing”; U.S. patent application Ser. No.17/089,305, entitled “Method and System for Interaction Servicing withEmbeddable Ribbon Display”; U.S. patent application Ser. No. 17/089,302,entitled “Method and System for Resolving Producer and ConsumerAffinities in Interaction Servicing”; U.S. patent application Ser. No.17/089,311, entitled “Method and System for Providing Resiliency inInteraction Servicing”; U.S. patent application Ser. No. 17/089,061,entitled “Method and System for Providing Resiliency in InteractionServicing Across Data Centers”; U.S. patent application Ser. No.17/089,093, entitled “Method and System for Providing Resiliency inInteraction Servicing Across Data Centers”; and U.S. patent applicationSer. No. 17/089,145, entitled “Method and System for Providing HighEfficiency, Bidirectional Messaging for Low Latency Applications,” thecontents of each of which is hereby incorporated by reference in itsrespective entirety.

BACKGROUND 1. Field of the Disclosure

This technology generally relates to methods and systems for performingcustomer service interactions, and more particularly to methods andsystems for integrating and streamlining large number of customerservice interactions to ensure efficient and accurate interactionservicing results.

2. Background Information

For a large corporate organization that has many customers, customerservice is an important aspect of the business operation. Customerstypically expect service requests to be handled in a timely and accuratemanner, and if the corporate organization fails to provide such customerservice, there may be a negative effect on the reputation of thatorganization.

Many customer service requests are performed online via the Internet.For such requests, it is important that the request be assessed androuted to the correct entity within the corporate organization, togetherwith all of the relevant information that will be needed by the entitythat will handle the request. However, the proper routing and handlingof such requests may be complicated when the number of requests is largeand the size of the corporate organization is large.

Accordingly, there is a need for a tool that integrates and streamlinesthe processing of customer service interactions in order to ensureefficient and accurate handling and resolution thereof.

SUMMARY

The present disclosure, through one or more of its various aspects,embodiments, and/or specific features or sub-components, provides, interalia, various systems, servers, devices, methods, media, programs, andplatforms for handling large number of customer service interactions toensure efficient and accurate interaction servicing results.

According to an aspect of the present disclosure, a method for servicinga plurality of interactions with users is provided. The method isimplemented by at least one processor. The method includes: receiving,by the at least one processor from each respective user, a respectiverequest for a corresponding interaction; obtaining, by the at least oneprocessor for each interaction, request-specific information thatrelates to the received respective request and user-specific informationthat relates to the respective user; analyzing, by the at least oneprocessor for each interaction, the request-specific information todetermine at least one corresponding microservice that is usable forhandling the interaction, and routing, by the at least one processor foreach interaction, the request-specific information and the user-specificinformation to a respective destination that relates to the determinedat least one corresponding microservice.

The method may further include receiving, by the at least one processorfrom the at least one corresponding microservice, response informationthat relates to a response to the respective request for thecorresponding interaction.

The method may further include displaying, by the at least processor forat least one interaction, a screen that includes at least a subset ofthe request-specific information, at least a subset of the user-specificinformation, and status information that relates to a status of theresponse to the respective request for the at least one interaction.

The method may further include determining, for each interaction, arequest type for each respective request, the request type including atleast one from among a voice request, an email request, an online chatrequest, a browser request, and a click-to-call request.

The analyzing may further include analyzing the request-specificinformation to determine at least two corresponding microservices thatare usable for handling the corresponding interaction.

The method may further include determining at least two separate routeshaving at least two different destinations that correspond to thedetermined at least two corresponding microservices; and using at leastone metric that relates to a workload distribution to select an optimumroute from among the determined at least two separate routes. Therouting may further include using the selected optimum route.

According to another exemplary embodiment, a method for providingresiliency in a telephony communication system is provided. The methodis implemented by at least one processor. The method includes:obtaining, by the at least one processor, a plurality of resources thatare available in a first data center: receiving, by the at least oneprocessor from a client, a request for accessing a first resource fromamong the plurality of resources; transmitting, by the at least oneprocessor to the client, a first Uniform Resource Locator (URL) thatincludes information for facilitating a client access to the firstresource in the first data center; when the first resource becomesunavailable in the first data center and available in a second datacenter, transmitting, by the at least one processor to the second datacenter, a subscribe message for facilitating a client access to thefirst resource in the second data center, and when the client access tothe first resource in the second data center becomes available in atleast one from among the first data center and the second data center,transmitting, by the at least one processor to the client, a second URLthat includes information for facilitating the client access to thefirst resource in the available at least one from among the first datacenter and the second data center.

When the first resource becomes unavailable in the first data center,the method may further include transmitting, to a client discoveryservice, a status message that includes an identification of the firstresource, an identification of the first data center, an identificationof an availability zone within the first data center at which the firstresource was previously available, an out-of-service status, and acurrent time.

When the first resource becomes unavailable in the first data center,the method may further include transmitting, to the client, a messageindicating that the first resource is temporarily unavailable.

When the first resource becomes available in the second data center, themethod may further include transmitting, to a client discovery service,a status message that includes an identification of the first resource,an identification of the second data center, an identification of anavailability zone within the second data center at which the firstresource has become available, an in-service status, and a current time.

According to yet another exemplary embodiment, a method for providingload-balancing for a service in a telephony communication system isprovided. The method is implemented by at least one processor. Themethod includes: partitioning, by the at least one processor, anallocation of a plurality of resources among a plurality of availabilityzones (AZs) within a first data center; and when a first AZ from amongthe plurality of AZs becomes unavailable, reallocating, by the at leastone processor, the plurality of resources among the AZs within theplurality of AZs that remain available. The partitioning includesassigning each respective resource to a primary AZ and to at least onesecondary AZ within the plurality of AZs.

The at least one processor may be configured to operate in conjunctionwith a topic and partition based message bus that includes at least onefrom among Kafka and Kinesis.

When a ResourceAssigned message is consumed from a primary topic, themethod may further include transmitting, by the at least one processor,the ResourceAssigned message from the primary AZ to at least onesecondary AZ via a backup topic; subscribing, by the at least oneprocessor, to an event source that corresponds to a resource that isidentified in the ResourceAssigned message; and persisting, by the atleast one processor, a primary mapping of a resource identifier to arequest topic partition index.

When a ResourceAssigned message is consumed from a backup topic, themethod may further include: subscribing, by the at least one processor,to an event source that corresponds to a resource that is identified inthe ResourceAssigned message; and persisting, by the at least oneprocessor, a backup mapping of a resource identifier to a backup topicpartition index.

According to still another exemplary embodiment, a method for providingresiliency with respect to a potential loss of an Kafka cluster isprovided. The method is implemented by at least one processor. Themethod includes: configuring, by the at least one processor, a topic oneach of a primary Kafka cluster and a backup Kafka cluster, such that aconsumer consumes from both of the primary Kafka cluster and the backupKafka cluster; attempting, by the at least one processor, to produce amessage to the primary Kafka cluster with a fail-to-send timeout; andwhen the message is not produced within the fail-to-send timeout,attempting, by the at least one processor, to produce the message to thebackup Kafka cluster.

The method may further include when the message is not produced to theprimary Kafka cluster within the fail-to-send timeout, indicating thatthe primary Kafka cluster is down with respect to at least one fromamong the topic and a topic-partition; monitoring the primary Kafkacluster with respect to the at least one from among the topic and thetopic-partition by querying for metadata, and when the metadata issuccessfully retrieved in response to a query, indicating that theprimary Kafka cluster is up with respect to the at least one from amongthe topic and the topic-partition.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in the detailed descriptionwhich follows, in reference to the noted plurality of drawings, by wayof non-limiting examples of preferred embodiments of the presentdisclosure, in which like characters represent like elements throughoutthe several views of the drawings.

FIG. 1 illustrates an exemplary computer system.

FIG. 2 illustrates an exemplary diagram of a network environment.

FIG. 3 shows an exemplary system for implementing a method for handlinglarge number of customer service interactions to ensure efficient andaccurate interaction servicing results.

FIG. 4 is a flowchart of an exemplary process for implementing a methodfor handling large number of customer service interactions to ensureefficient and accurate interaction servicing results.

FIG. 5 is a first screenshot that illustrates a user interface forhandling a customer interaction, according to an exemplary embodiment.

FIG. 6 is a second screenshot that illustrates customer identificationinformation that is displayable on the user interface for handling acustomer interaction, according to an exemplary embodiment.

FIG. 7 is a diagram that illustrates a plurality of microservices andcorresponding routing paths for implementing a method for handling largenumber of customer service interactions to ensure efficient and accurateinteraction servicing results, according to an exemplary embodiment.

FIG. 8 is a flowchart of a method for providing resiliency in atelephony communication system, according to an exemplary embodiment.

FIG. 9 is a flowchart of a method for providing load-balancing for aservice in a telephony communication system, according to an exemplaryembodiment.

FIG. 10 is a flowchart of a method for providing resiliency with respectto a potential loss of a cluster of an Kafka stream processing platform,according to an exemplary embodiment.

DETAILED DESCRIPTION

Through one or more of its various aspects, embodiments and/or specificfeatures or sub-components of the present disclosure, are intended tobring out one or more of the advantages as specifically described aboveand noted below.

The examples may also be embodied as one or more non-transitory computerreadable media having instructions stored thereon for one or moreaspects of the present technology as described and illustrated by way ofthe examples herein. The instructions in some examples includeexecutable code that, when executed by one or more processors, cause theprocessors to carry out steps necessary to implement the methods of theexamples of this technology that are described and illustrated herein.

FIG. 1 is an exemplary system for use in accordance with the embodimentsdescribed herein. The system 100 is generally shown and may include acomputer system 102, which is generally indicated.

The computer system 102 may include a set of instructions that can beexecuted to cause the computer system 102 to perform any one or more ofthe methods or computer-based functions disclosed herein, either aloneor in combination with the other described devices. The computer system102 may operate as a standalone device or may be connected to othersystems or peripheral devices. For example, the computer system 102 mayinclude, or be included within, any one or more computers, servers,systems, communication networks or cloud environment. Even further, theinstructions may be operative in such cloud-based computing environment.

In a networked deployment, the computer system 102 may operate in thecapacity of a server or as a client user computer in a server-clientuser network environment, a client user computer in a cloud computingenvironment, or as a peer computer system in a peer-to-peer (ordistributed) network environment. The computer system 102, or portionsthereof, may be implemented as, or incorporated into, various devices,such as a personal computer, a tablet computer, a set-top box, apersonal digital assistant, a mobile device, a palmtop computer, alaptop computer, a desktop computer, a communications device, a wirelesssmart phone, a personal trusted device, a wearable device, a globalpositioning satellite (GPS) device, a web appliance, a device that isrunning the Apple iOS operating system, a device that is running theAndroid operating system, a device that is capable of running a webbrowser to connect to the Internet. or any other machine capable ofexecuting a set of instructions (sequential or otherwise) that specifyactions to be taken by that machine. Further, while a single computersystem 102 is illustrated, additional embodiments may include anycollection of systems or sub-systems that individually or jointlyexecute instructions or perform functions. The term “system” shall betaken throughout the present disclosure to include any collection ofsystems or sub-systems that individually or jointly execute a set, ormultiple sets, of instructions to perform one or more computerfunctions.

As illustrated in FIG. 1, the computer system 102 may include at leastone processor 104. The processor 104 is tangible and non-transitory. Asused herein, the term “non-transitory” is to be interpreted not as aneternal characteristic of a state, but as a characteristic of a statethat will last for a period of time. The term “non-transitory”specifically disavows fleeting characteristics such as characteristicsof a particular carrier wave or signal or other forms that exist onlytransitorily in any place at any time. The processor 104 is an articleof manufacture and/or a machine component. The processor 104 isconfigured to execute software instructions in order to performfunctions as described in the various embodiments herein. The processor104 may be a general-purpose processor or may be part of an applicationspecific integrated circuit (ASIC) The processor 104 may also be amicroprocessor, a microcomputer, a processor chip, a controller, amicrocontroller, a digital signal processor (DSP), a state machine, or aprogrammable logic device. The processor 104 may also be a logicalcircuit, including a programmable gate array (PGA) such as a fieldprogrammable gate array (FPGA), or another type of circuit that includesdiscrete gate and/or transistor logic. The processor 104 may be acentral processing unit (CPU), a graphics processing unit (GPU), orboth. Additionally, any processor described herein may include multipleprocessors, parallel processors, or both. Multiple processors may beincluded in, or coupled to, a single device or multiple devices.

The computer system 102 may also include a computer memory 106. Thecomputer memory 106 may include a static memory, a dynamic memory, orboth in communication. Memories described herein are tangible storagemediums that can store data as well as executable instructions and arenon-transitory during the time instructions are stored therein. Again,as used herein, the term “non-transitory” is to be interpreted not as aneternal characteristic of a state, but as a characteristic of a statethat will last for a period of time. The term “non-transitory”specifically disavows fleeting characteristics such as characteristicsof a particular carrier wave or signal or other forms that exist onlytransitorily in any place at any time. The memories are an article ofmanufacture and/or machine component. Memories described herein arecomputer-readable mediums from which data and executable instructionscan be read by a computer. Memories as described herein may be randomaccess memory (RAM), read only memory (ROM), flash memory, electricallyprogrammable read only memory (EPROM), electrically erasableprogrammable read-only memory (EEPROM), registers, a hard disk, a cache,a removable disk, tape, compact disk read only memory (CD-ROM), digitalversatile disk (DVD), floppy disk, blu-ray disk, or any other form ofstorage medium known in the art. Memories may be volatile ornon-volatile, secure and/or encrypted, unsecure and/or unencrypted. Ofcourse, the computer memory 106 may comprise any combination of memoriesor a single storage.

The computer system 102 may further include a display 108, such as aliquid crystal display (LCD), an organic light emitting diode (OLED), aflat panel display, a solid state display, a cathode ray tube (CRT), aplasma display, or any other type of display, examples of which are wellknown to skilled persons.

The computer system 102 may also include at least one input device 110,such as a keyboard, a touch-sensitive input screen or pad, a speechinput, a mouse, a remote control device having a wireless keypad, amicrophone coupled to a speech recognition engine, a camera such as avideo camera or still camera, a cursor control device, a globalpositioning system (GPS) device, an altimeter, a gyroscope, anaccelerometer, a proximity sensor, or any combination thereof. Thoseskilled in the art appreciate that various embodiments of the computersystem 102 may include multiple input devices 110. Moreover, thoseskilled in the art further appreciate that the above-listed, exemplaryinput devices 110 are not meant to be exhaustive and that the computersystem 102 may include any additional, or alternative, input devices110.

The computer system 102 may also include a medium reader 112 which isconfigured to read any one or more sets of instructions, e.g. software,from any of the memories described herein. The instructions, whenexecuted by a processor, can be used to perform one or more of themethods and processes as described herein. In a particular embodiment,the instructions may reside completely, or at least partially, withinthe memory 106, the medium reader 112, and/or the processor 110 duringexecution by the computer system 102.

Furthermore, the computer system 102 may include any additional devices,components, parts, peripherals, hardware, software or any combinationthereof which are commonly known and understood as being included withor within a computer system, such as, but not limited to, a networkinterface 114 and an output device 116. The output device 116 may be,but is not limited to, a speaker, an audio out, a video out, aremote-control output, a printer, or any combination thereof.

Each of the components of the computer system 102 may be interconnectedand communicate via a bus 118 or other communication link. Asillustrated in FIG. 1, the components may each be interconnected andcommunicate via an internal bus. However, those skilled in the artappreciate that any of the components may also be connected via anexpansion bus. Moreover, the bus 118 may enable communication via anystandard or other specification commonly known and understood such as,but not limited to, peripheral component interconnect, peripheralcomponent interconnect express, parallel advanced technology attachment,serial advanced technology attachment, etc.

The computer system 102 may be in communication with one or moreadditional computer devices 120 via a network 122. The network 122 maybe, but is not limited to, a local area network, a wide area network,the Internet, a telephony network, a short-range network, or any othernetwork commonly known and understood in the art. The short-rangenetwork may include, for example, Bluetooth, Zigbee, infrared, nearfield communication, ultraband, or any combination thereof. Thoseskilled in the art appreciate that additional networks 122 which areknown and understood may additionally or alternatively be used and thatthe exemplary networks 122 are not limiting or exhaustive. Also, whilethe network 122 is illustrated in FIG. 1 as a wireless network, thoseskilled in the art appreciate that the network 122 may also be a wirednetwork.

The additional computer device 120 is illustrated in FIG. 1 as apersonal computer. However, those skilled in the art appreciate that, inalternative embodiments of the present application, the computer device120 may be a laptop computer, a tablet PC, a personal digital assistant,a mobile device, a palmtop computer, a desktop computer, acommunications device, a wireless telephone, a personal trusted device,a web appliance, a server, a device that is running the Apple iOSoperating system, a device that is running the Android operating system,a device that is capable of running a web browser to connect to theInternet, or any other device that is capable of executing a set ofinstructions, sequential or otherwise, that specify actions to be takenby that device. Of course, those skilled in the art appreciate that theabove-listed devices are merely exemplary devices and that the device120 may be any additional device or apparatus commonly known andunderstood in the art without departing from the scope of the presentapplication. For example, the computer device 120 may be the same orsimilar to the computer system 102. Furthermore, those skilled in theart similarly understand that the device may be any combination ofdevices and apparatuses.

Of course, those skilled in the art appreciate that the above-listedcomponents of the computer system 102 are merely meant to be exemplaryand are not intended to be exhaustive and/or inclusive. Furthermore, theexamples of the components listed above are also meant to be exemplaryand similarly are not meant to be exhaustive and/or inclusive.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented using a hardware computersystem that executes software programs. Further, in an exemplary,non-limited embodiment, implementations can include distributedprocessing, component/object distributed processing, and parallelprocessing. Virtual computer system processing can be constructed toimplement one or more of the methods or functionalities as describedherein, and a processor described herein may be used to support avirtual processing environment.

As described herein, various embodiments provide optimized methods andsystems for handling large number of customer service interactions toensure efficient and accurate interaction servicing results.

Referring to FIG. 2, a schematic of an exemplary network environment 200for implementing a method for handling large number of customer serviceinteractions to ensure efficient and accurate interaction servicingresults is illustrated. In an exemplary embodiment, the method isexecutable on any networked computer platform, such as, for example, apersonal computer (PC), a device that is running the Apple iOS operatingsystem, a device that is running the Android operating system, or adevice that is capable of running a web browser to connect to theInternet.

The method for handling large number of customer service interactions toensure efficient and accurate interaction servicing results may beimplemented by an Interaction Servicing Fabric (ISF) device 202. The ISFdevice 202 may be the same or similar to the computer system 102 asdescribed with respect to FIG. 1. The ISF device 202 may store one ormore applications that can include executable instructions that, whenexecuted by the ISF device 202, cause the ISF device 202 to performactions, such as to transmit, receive, or otherwise process networkmessages, for example, and to perform other actions described andillustrated below with reference to the figures. The application(s) maybe implemented as modules or components of other applications. Further,the application(s) can be implemented as operating system extensions,modules, plugins, or the like.

Even further, the application(s) may be operative in a cloud-basedcomputing environment. The application(s) may be executed within or asvirtual machine(s) or virtual server(s) that may be managed in acloud-based computing environment. Also, the application(s), and eventhe ISF device 202 itself, may be located in virtual server(s) runningin a cloud-based computing environment rather than being tied to one ormore specific physical network computing devices. Also, theapplication(s) may be running in one or more virtual machines (VMs)executing on the ISF device 202. Additionally, in one or moreembodiments of this technology, virtual machine(s) running on the ISFdevice 202 may be managed or supervised by a hypervisor.

In the network environment 200 of FIG. 2, the ISF device 202 is coupledto a plurality of server devices 204(1)-204(n) that hosts a plurality ofdatabases 206(1)-206(n), and also to a plurality of client devices208(1)-208(n) via communication network(s) 210. A communicationinterface of the ISF device 202, such as the network interface 114 ofthe computer system 102 of FIG. 1, operatively couples and communicatesbetween the ISF device 202, the server devices 204(1)-204(n), and/or theclient devices 208(1)-208(n), which are all coupled together by thecommunication network(s) 210, although other types and/or numbers ofcommunication networks or systems with other types and/or numbers ofconnections and/or configurations to other devices and/or elements mayalso be used.

The communication network(s) 210 may be the same or similar to thenetwork 122 as described with respect to FIG. 1, although the ISF device202, the server devices 204(1)-204(n), and/or the client devices208(1)-208(n) may be coupled together via other topologies Additionally,the network environment 200 may include other network devices such asone or more routers and/or switches, for example, which are well knownin the art and thus will not be described herein. This technologyprovides a number of advantages including methods, non-transitorycomputer readable media, and ISF devices that efficiently implementmethods and systems for handling large number of customer serviceinteractions to ensure efficient and accurate interaction servicingresults.

By way of example only, the communication network(s) 210 may includelocal area network(s) (LAN(s)) or wide area network(s) (WAN(s)), and canuse TCP/IP over Ethernet and industry-standard protocols, although othertypes and/or numbers of protocols and/or communication networks may beused. The communication network(s) 210 in this example may employ anysuitable interface mechanisms and network communication technologiesincluding, for example, teletraffic in any suitable form (e.g, voice,modem, and the like), Public Switched Telephone Network (PSTNs),Ethernet-based Packet Data Networks (PDNs), combinations thereof, andthe like.

The ISF device 202 may be a standalone device or integrated with one ormore other devices or apparatuses, such as one or more of the serverdevices 204(1)-204(n), for example. In one particular example, the ISFdevice 202 may include or be hosted by one of the server devices204(1)-204(n), and other arrangements are also possible. Moreover, oneor more of the devices of the ISF device 202 may be in a same or adifferent communication network including one or more public, private,or cloud networks, for example.

The plurality of server devices 204(1)-204(n) may be the same or similarto the computer system 102 or the computer device 120 as described withrespect to FIG. 1, including any features or combination of featuresdescribed with respect thereto. For example, any of the server devices204(1)-204(n) may include, among other features, one or more processors,a memory, and a communication interface, which are coupled together by abus or other communication link, although other numbers and/or types ofnetwork devices may be used. The server devices 204(1)-204(n) in thisexample may process requests received from the ISF device 202 via thecommunication network(s) 210 according to the HTTP-based and/orJavaScript Object Notation (JSON) protocol, for example, although otherprotocols may also be used.

The server devices 204(1)-204(n) may be hardware or software or mayrepresent a system with multiple servers in a pool, which may includeinternal or external networks. The server devices 204(1)-204(n) hoststhe databases 206(1)-206(n) that are configured to store data thatrelates to user requests, identification information that relates toindividual users, and microservices that are used for resolving userrequests.

Although the server devices 204(1)-204(n) are illustrated as singledevices, one or more actions of each of the server devices 204(1)-204(n)may be distributed across one or more distinct network computing devicesthat together comprise one or more of the server devices 204(1)-204(n)Moreover, the server devices 204(1)-204(n) are not limited to aparticular configuration. Thus, the server devices 204(1)-204(n) maycontain a plurality of network computing devices that operate using amaster/slave approach, whereby one of the network computing devices ofthe server devices 204(1)-204(n) operates to manage and/or otherwisecoordinate operations of the other network computing devices.

The server devices 204(1)-204(n) may operate as a plurality of networkcomputing devices within a cluster architecture, a peer-to peerarchitecture, virtual machines, or within a cloud architecture, forexample. Thus, the technology disclosed herein is not to be construed asbeing limited to a single environment and other configurations andarchitectures are also envisaged.

The plurality of client devices 208(1)-208(n) may also be the same orsimilar to the computer system 102 or the computer device 120 asdescribed with respect to FIG. 1, including any features or combinationof features described with respect thereto. For example, the clientdevices 208(1)-208(n) in this example may include any type of computingdevice that can interact with the ISF device 202 via communicationnetwork(s) 210. Accordingly, the client devices 208(1)-208(n) may bemobile computing devices, desktop computing devices, laptop computingdevices, tablet computing devices, virtual machines (includingcloud-based computers), or the like, that host chat, e-mail, orvoice-to-text applications, for example. In an exemplary embodiment, atleast one client device 208 is a wireless mobile communication device,i.e., a smart phone.

The client devices 208(1)-208(n) may run interface applications, such asstandard web browsers or standalone client applications, which mayprovide an interface to communicate with the ISF device 202 via thecommunication network(s) 210 in order to communicate user requests andinformation. The client devices 208(1)-208(n) may further include, amongother features, a display device, such as a display screen ortouchscreen, and/or an input device, such as a keyboard, for example.

Although the exemplary network environment 200 with the ISF device 202,the server devices 204(1)-204(n), the client devices 208(1)-208(n), andthe communication network(s) 210 are described and illustrated herein,other types and/or numbers of systems, devices, components, and/orelements in other topologies may be used. It is to be understood thatthe systems of the examples described herein are for exemplary purposes,as many variations of the specific hardware and software used toimplement the examples are possible, as will be appreciated by thoseskilled in the relevant an(s).

One or more of the devices depicted in the network environment 200, suchas the ISF device 202, the server devices 204(1)-204(n), or the clientdevices 208(1)-208(n), for example, may be configured to operate asvirtual instances on the same physical machine. In other words, one ormore of the ISF device 202, the server devices 204(1)-204(n), or theclient devices 208(1)-208(n) may operate on the same physical devicerather than as separate devices communicating through communicationnetwork(s) 210. Additionally, there may be more or fewer ISF devices202, server devices 204(1)-204(n), or client devices 208(1)-208(n) thanillustrated in FIG. 2.

In addition, two or more computing systems or devices may be substitutedfor any one of the systems or devices in any example. Accordingly,principles and advantages of distributed processing, such as redundancyand replication also may be implemented, as desired, to increase therobustness and performance of the devices and systems of the examples.The examples may also be implemented on computer system(s) that extendacross any suitable network using any suitable interface mechanisms andtraffic technologies, including by way of example only teletraffic inany suitable form (e.g, voice and modem), wireless traffic networks,cellular traffic networks, Packet Data Networks (PDNs), the Internet,intranets, and combinations thereof.

The ISF device 202 is described and illustrated in FIG. 3 as includingan interaction services routing and handling module 302, although it mayinclude other rules, policies, modules, databases, or applications, forexample. As will be described below, the interaction services routingand handling module 302 is configured to implement a method for handlinglarge number of customer service interactions to ensure efficient andaccurate interaction servicing results.

An exemplary process 300 for implementing a mechanism for handling largenumber of customer service interactions to ensure efficient and accurateinteraction servicing results by utilizing the network environment ofFIG. 2 is illustrated as being executed in FIG. 3. Specifically, a firstclient device 208(1) and a second client device 208(2) are illustratedas being in communication with ISF device 202. In this regard, the firstclient device 208(1) and the second client device 208(2) may be“clients” of the ISF device 202 and are described herein as such.Nevertheless, it is to be known and understood that the first clientdevice 208(1) and/or the second client device 208(2) need notnecessarily be “clients” of the ISF device 202, or any entity describedin association therewith herein.

Any additional or alternative relationship may exist between either orboth of the first client device 208(1) and the second client device208(2) and the ISF device 202, or no relationship may exist. Forexample, the ISF device 202 and the first client device 208(1) may beconfigured as the same physical device.

Further, ISF device 202 is illustrated as being able to access amicroservices data repository 206(1) and a user-specific identificationinformation database 206(2). The interaction services routing andhandling module 302 may be configured to access these databases forimplementing a method for handling large number of customer serviceinteractions to ensure efficient and accurate interaction servicingresults.

The first client device 208(1) may be, for example, a smart phone. Ofcourse, the first client device 208(1) may be any additional devicedescribed herein. The second client device 208(2) may be, for example, apersonal computer (PC). Of course, the second client device 208(2) mayalso be any additional device described herein.

The process may be executed via the communication network(s) 210, whichmay comprise plural networks as described above. For example, in anexemplary embodiment, either or both of the first client device 208(1)and the second client device 208(2) may communicate with the ISF device202 via broadband or cellular communication. Alternatively, the processmay be executed by the ISF device 202 in a standalone manner, e.g., by asmart phone on which the interaction services routing and handlingmodule 302 has been downloaded. Of course, these embodiments are merelyexemplary and are not limiting or exhaustive.

Upon being started, a processor that is hosted in the ISF device 202executes a process for handling large number of customer serviceinteractions to ensure efficient and accurate interaction servicingresults. An exemplary process for handling large number of customerservice interactions to ensure efficient and accurate interactionservicing results is generally indicated at flowchart 400 in FIG. 4.

In process 400 of FIG. 4, at step S402, the interaction services routingand handling module 302 receives, from each of a plurality of users, arespective request for a corresponding interaction. At step S404, theinteraction services routing and handling module 302 obtainsrequest-specific information that relates to each respective request anduser-specific information that relates to each respective user. In anexemplary embodiment, the interaction services routing and handlingmodule 302 prompts each user to enter the user-specific information viaa graphical user interface that is displayed on the screen of a clientdevice 208.

Further, the interaction services routing and handling module 302 mayalso display, on a screen of the IDF device 202, a user interface forhandling an interaction request that includes at least a subset of therequest-specific information and at least a subset of the user-specificinformation. For example, referring to FIG. 5, a first screenshot 500that illustrates a user interface for handling a customer interactionmay include a task bar at the top of the screen, a trapezoidal-shapedribbon that includes request-specific information and user-specificinformation at the top right-hand portion of the screen, a menu and alist of recent interactions along the left side of the screen, andstatus information relating to the current interaction request in thebody of the screen. As another example, referring to FIG. 6, a secondscreenshot 600 that illustrates the user interface may include moredetails of the user-specific information, together with thetrapezoidal-shaped ribbon shown in FIG. 5.

At step S406, the interaction services routing and handling module 302determines, for each interaction, a request type for each respectiverequest. The request type may indicate a communication mode by which aparticular request is received. In an exemplary embodiment, the requesttype may include at least one of a voice request, an email request, anonline chat request, a browser request, and a click-to-call request.

At step S408, the interaction services routing and handling module 302analyzes, for each requested interaction, the request-specificinformation in order to determine at least one correspondingmicroservice and/or at least one microservice instance that is usablefor handling the interaction. In an exemplary embodiment, theinteraction services routing and handling module may determine more thanone such microservice. For example, there may be any number ofmicroservices that are suitable for handling different aspects of aninteraction, such as two (2), three (3), five (5), ten (10), twenty(20), fifty (50), one hundred (100), or more such microservices; andsome of these may have overlapping functions. As another example, theremay be multiple microservice instances, which refers to using oneparticular microservice multiple times.

At step S410, the interaction services routing and handling module 302determines at least one suitable route for transmitting therequest-specific information and the user-specific information for eachrespective interaction to a respective destination that relates to themicroservices determined in step S408. In an exemplary embodiment, forany given interaction, there may be more than one suitable route andmore than one suitable destination, depending on the microservices to beused, and also depending on the order of using the microservices. As aresult, the interaction services routing and handling module 302 maydetermine two or more suitable routes and/or two or more suitabledestinations for a particular interaction. Then, at step S412, theinteraction services routing and handling module 302 uses a metric thatrelates to workload distribution for selecting an optimum route; and atstep S414, the interaction services routing and handling module 302 usesthe optimum route for routing the information.

FIG. 7 is a diagram 700 that illustrates a plurality of microservicesand corresponding routing paths for implementing a method for handlinglarge number of customer service interactions to ensure efficient andaccurate interaction servicing results, according to an exemplaryembodiment. As illustrated in FIG. 7, a large number of microservicesmay be available for handling a particular request with respect to aninteraction, including microservices having the following descriptors“resource state”, “attribution”, “event listener”; “auditor”; “warmchannel transfer”; “qualification”; “resource assign”; “eventprocessor”; “monitor”; “flow processor”: “channel adapters”; “rulesprocessor”; “get customer journey”; “specialist login”: “get specialistprofile”; “get contacts”; “get communication history”; “receive voice &video call”: “invoke automated chat”, “invoke social”; “auditor”,“invoke simple chat”; “invoke conversation (multimedia)”; setdisposition”; and “get customer journey”.

Further, as also illustrated in FIG. 7 and in accordance with anexemplary embodiment, the microservices may be depicted in ahoneycomb-type hexagonal pattern. In this manner, the analyzing of aparticular interaction effectively breaks up the associated tasks intorelatively small pieces that correspond to different microservices. Inan exemplary embodiment, a cloud native microservices-basedimplementation, such as Kafka, is used, and in this construct, thehoneycombs communicate with one other via events. The use of such animplementation provides several advantages, including the following: 1)Events must arrive in the proper order and must be scalable. 2) Bypartitioning the interactions, there is a low latency with respect toincreasing or decreasing the number of microservices to be used (furthernoting that lower processing latency may be achieved by increasing thenumber of microservice instances). 3) By virtue of the ordering and thescalability of events, the interaction services handling module 302achieves a higher throughput, thereby speeding up processing. 4) Loadbalancing and caching of IP addresses also contributes to higherprocessing speeds. 5) The ability to identify, multiple redundancies inconnections between microservices provides system resiliency androbustness. In an exemplary embodiment, events relating to a specificuser session must be consumed in exactly the same order as the eventswere produced. Events relating to multiple user sessions need not beconsumed, relative to each other, in the order in which they wereproduced. Distinguishing between events relating to a specific usersession and events relating to multiple user sessions in this manner mayfacilitate a greater parallel processing capacity.

At step S416, the interaction services routing and handling module 302receives response information that relates to a respective response foreach corresponding request. In this aspect, in many situations, thereceived response effectively concludes the interaction.

In an exemplary embodiment, a cloud native microservice approach for anomni-channel contact center is provided. This approach includesdecomposed contract bases microservices and a microservices-basedevent-driven architecture that resides in the cloud and is designed tohave an elastic scale, high availability, and high resiliency, with aservice level agreement (SLA) that is higher than 99.999%. The contactcenter is a real time (millisecond, sub-second latency) architecturethat has an extensive intrinsic design. Groups of microservices arecreated in order to provide different aspects of functionality. Thestack includes a platform as a service (i.e., microservices platform,such as, for example, Kubernetes or Cloud Foundry), Kafka scalable eventmessaging and streaming technology, Cassandra, NoSQL performant privatedatabase for microservices, and distributed in-memory grid technologiessuch as, for example, Cloud Cache, for storing quickly accessible stateinformation.

The general architecture includes a facade layer of microservicesadapting to external vendor elements through predetermined protocols,and normalizing the communication to fit a highly available, concurrentprocessing, resilient, large-scale, event-based communication, KafkaTopics for ordered events to consuming instances of microservices;client-facing microservices which consume raw Kafka events from façademicroservices and provide discrete functional services with aclient-facing application programming interface (API)—RESTful WebServices; a general purpose notification service that provides abidirectional low latency event exchange mechanism between clients(e.g., single user web clients) or server applications (e.g., fraudecosystems, voice biometric systems, analytics, and/or recordingsystems); web clients following microservices architecture with userinterface (UI), software development kit (SDK), and Servicesarchitecture using Angular8 frameworks; drop-in concept for specialistphone control applications into various servicing applicationsdelivering a computer telephony integration (CTI) container with all ofthe functionality included therein; programmatic APIs for screen pop;and standalone ribbon Clusters of microservices are provided for coreservicing fabric telephony and agent login, automated specialistprovisioning across multiple vendor solutions for orchestration,routing, recording, voicemail, and other functionalities; specialistphone control, and real-time dashboard for contact center supervisorypersonnel.

In another exemplary embodiment, a client ribbon embedding mechanismthat is suitable for a large scale deployment and integration with keyvalue pairs (KVPs) for screen pops is provided. The client ribbonembedding mechanism includes a self-contained feature set that isextensible to omni-channel without requiring extensive deployment andknowledge of CTI protocols and APIs by non-contact center developers.The mechanism creates a lightweight approach to integrating contactcenter specialist features into the servicing application, therebyproviding a quicker rollout, reduced integration effort, and automaticupdates for easier maintenance. The mechanism includes standardizedintegration patterns and a cookbook recipe approach, and provides a wayto obtain integrated features required by servicing applications. Thesefeatures may include: screen pops, updating customer relevant data: endcall tracking; state change tied to case disposition; transfer andconference events; customized call notifications; and enabling key valueobservers (KVOs) to be updated by servicing applications, middleware,and fraud authentication systems.

In yet another exemplary embodiment, a Kafka usage for conveningstateful ordered events to stateless, scalable eventing in real time isprovided. The design includes concurrent data-center (DC) andpool-specific active and backup topics on multiple Kafka clusters inorder to handle catastrophic pool failures. In an exemplary embodiment,a pool refers to an instance of the cloud platform so that multiplepools within a DC provide resiliency in the event of a failure of asingle pool (e.g, a bad network router). In the present disclosure, a“pool” is equivalent to an Availability Zone (AZ) within a DC, and assuch, the terms “pool” and “AZ” are used interchangeably herein. Otherfeatures include cross-DC Kafka events to provide a telephony servicethat is abstracted from an affinity to one of many DC's. The use of aKafka routing key that is tied to directory numbers (DNs) and design inpartitioning may also be provided, in order to cause ordered events togo to particular consumers in a scalable manner. A sticky Kafkapartition assignor to reduce latencies when the cloud systemautomatically scales up or down may also be provided, for overcoming aneed to rebalance and/or resend on multiple hops that may otherwiseintroduce latencies. A sequential thread executor may also be providedto distinguish between events that may be processed in parallel fromthose that must be processed sequentially.

The Kafka usage may include a sticky pool-aware Kafka partition assignorto enable a cloud system to automatically scale up or down despite poolaffinities, which require each message to be processed by an instancewithin that pool that would otherwise fail or be inefficient outside ofthat pool. The sticky pool-aware Kafka partition assignor is designed tominimize churn while allowing an application to reserve a partition inorder to avoid any impact while scaling up. The sticky pool-aware Kafkapartition assignor may also cause partitions to stick to respectivepools so that affinities to each pool are unaffected during rebalancing.

The Kafka usage may also provide for handling affinities at the edge ofthe cloud where only one instance can process a particular message butKafka has only crude routing capabilities. In this aspect, anapplication instance with an affinity, such as, for example, aweb-socket to a specific client, supplies the client with asubscriptionId that happens to also be a Kafka routing key thatguarantees that all messages sent to that client from back end servicesarrive, within a single hop, at the correct application instance. Theapplication had previously reserved a partition, calculated as at leastone universally unique identifier (UUID) that routes to the partition,so that the UUID(s) can be offered on demand to clients as subscriptionIDs.

The Kafka usage may also provide for multi-threading of the consumptionof messages per Kafka partition while maintaining strict messageordering. In this aspect, for the vast majority of application, orderingonly has meaning for messages produced with the same routing-key. Thus,the Kafka usage may be designed to process all messages received from apartition in parallel except for those messages with the same key whichmust be processed sequentially.

In still another exemplary embodiment, resiliency patterns and a clientdiscovery service designed to overcome global load balancer (GLB)latencies is provided. Browsers and client desktops cache domain namesystem (DNS) resolution of uniform resource locators (URLs), and whenthe backend services or pools experience failures, the clients continueto attempt to generate requests to the same defunct destination. In suchdeployments, where no performant IP sprayers or gateways exist and wheremillisecond latency SLAs exit, there may be a disruption in thecontinuous availability of services. In this aspect, a client sideresiliency that complements the multi-pool, multi-instance, andmulti-data center availability for instant seamless connection isprovided. The client first discovers services and capabilities,including backup pool URLs, according to current availability and userauthorization. The discovery service provides intelligent backup URLsfor stateful services, stateless services, and external server systems Aclient software development kit abstracts the resiliency, rehydration,and reconnection logic, begins network recovery, and then does aseamless login. The client user interface automatically recovers fromthe loss of a websocket or failure of a cloud microservice in a pool.

In yet another exemplary embodiment, resiliency patterns and seamlessresiliency of stateful, low latency telephony clients across multipledata centers (DCs). In each data center, stateful edge services monitoreach extension (i.e., domain name) simultaneously from differentinstances on both pools, thereby providing both instance and poolresiliency. Such services may use a de-duper that receives events fromboth pools but propagates only one pool. For phone resiliency, extension(domain name) may move from one data center to another, and theservicing fabric in both data centers may detect the move and directrequests to the new data center. Failure to login causes aresynchronization of the phone state in both data centers, thusself-healing in case discovery becomes out of synchronization.

The following table provides a list of features and specific aspectsthereof:

Stateful Domain Stateful → Bidirectional Dealing with Follow the Phone -Stateless WebSocket Vendor Egress DR failover High Affinity connectionsLow Latency Minimize Select Blazing Highly concurrent Custom StickyLatencies through Fast Technologies connections: Kafka Partitioncolocation vendor systems & Assignor clients Stack HA Provide HighLeverage nascent Event Starters Standby Data Availability (HA)resiliency in stack encapsulate High Center (DC) of CaaS, KafkaAvailability (HA) Promotion clusters under the cover Load BalancingCircuit Breaker Connection to Phone and queue Data extractions Patterns:for end- Global Load monitoring load load balanced user client andBalancers (GLBs) balanced across a across Data server-to-server fornon-cloud DC Centers (DCs) (API2API) servers invocations, with backupAvailability Zones Black Availability Client Side Kafka moves allSubscriptions SDK connects to Zone Failure Recovery (Web load to otherreplicated across other Availability Socket disconnect, AvailabilityZone Availability Zones Zone Availability Zone in less than 3 secfailure, app failure) Grey Availability AZ aware Sticky Multiple layersof OAUTH2 Cloud Config Zone Failure Partition Assignor defense for greyAuthorization Server has all the isolates network failures acrossmultiple bootstrap info, issues in Availability Zone Prod: BitbucketAvailability Zones environment

In still another exemplary embodiment, defense mechanisms for handlinggrey failures in the cloud are provided. A first defense mechanism is asticky partitioner that is designed to handle a scenario in which onepool is bad, and even while sharing the same Kafka and Cassandra acrosstwo pools, events would zigzag across applications in the two pool,thereby increasing the probability of a grey failure when anymicroservice in a second pool begins to go bad, and also affecting alltraffic. The sticky partitioner addresses this scenario by isolatingnetwork issues in pools by primarily routing the events to the samepool, thereby ensuring that 50% of the traffic is not affected by anunhealthy grey pool.

A second defense mechanism is the use of multiple levels of defense forgrey failures so that a single failure does not equate to a requestfailure as it is retried across other pools and/or other mechanisms. Forexample, for a scenario in which an external server application issues arequest to a pool that is only partially able to service the request,thereby resulting in a failure, this defense mechanism is designed topropagate all information available for servicing the request in asecond attempt on another pool. If the second pool is able to find theremaining missing data from the first pool, then the second poolprocesses the request.

A third defense mechanism is the use of multiple layers of defense forgrey failures for stateful applications so that a single failure doesnot equate to a request failure as there are multiple resiliency designsat each stage of the microservice in order to ensure servicing therequest. For example, for a scenario in which a ribbon login failsbecause a CTI extension monitoring had failed or was interrupted, orbecause the request was routed to the wrong pool, or because the domainname is not in service, this defense mechanism is designed to performseveral functions, including the following: CTI monitors domain namechanges at all times; domain name in-service and out-of-service eventsare propagated across both data centers; if the login attempt comes to adata center where the domain name is out of service, CTI will ask theother data center's CTI to publish if the domain name is in service inthat data center; repeat a set up from scratch for failed connectionsfor some CTI domain names; delegate some failed connections for some CTIdomain names from one CTI to a backup CTI; and recovery code in ribbonclient to go into retry mode and determine when the domain name statuschanges, thereby self-healing.

In yet another exemplary embodiment, high efficiency reliablebidirectional messaging for low latency applications is provided. Thisembodiment includes several features. A first feature is an ability tosend a Kafka event direct to the instance hosting the web-socket for thefinal leg of delivery with a minimum possible latency. This is achievedby calculating a UUID that maps to a partition owned by thenotification-service instance so that all messages sent using that UUIDas a Kafka routing key are delivered directly to the correct one of manynotification-service instances.

A second feature is an ability to scale up a number of instances withoutany latency nor disruption to existing web-socket users. This isachieved by using a custom stick partition assignor whereby the consumeris guaranteed that one partition is never removed. This also avoidstwo-hop routing.

A third feature is load balancing of system-wide events to anotherecosystem through stateless, load balanced, randomized delivery on anyof the web-sockets (WS) This feature provides an ability to load-balanceevents that can be consumed by a group of web-socket clients. This isachieved by allowing each member of a load-balancing (LB) group tosubscribe with the name of the LB group so that future messages receivedby a notification service on a UUID that belongs to the group can bedelivered to any member.

A fourth feature allows for more than one web-socket to be part of ahigh availability (HA) group to ensure low latency and guaranteeddelivery on a surviving web-socket. This feature provides an ability tosupport clients that require a highly available pair of web-socketswhere ordered events are delivered via an “active web-socket” only, andwhen it fails, the surviving web-socket is immediately promoted to beingactive. Thus, a latency that would have occurred without the HA group iscompletely avoided. Meanwhile, the client will initiate a new backupweb-socket. To protect against failure or down-scaling, upon receiving anew web-socket request with an HA group identification, thecorresponding notification service will reject a request to create asecond web-socket in the same HA group on the same instance.

A fifth feature provides an ability to support message delivery fromclients in multiple pools. This is achieved by using Kafka's nativeability to route messages using a routing key so that the producer ofthe message only needs to know the Kafka cluster address.

A sixth feature provides an ability to subscribe anywhere, replicateeverywhere, and notify anywhere. This feature further provides anability to support message delivery from clients in multiple datacenters (DCs) whereby when a message is received in one DC where theUUID is not recognized, the notification service will query a databaseto determine the Kafka cluster associated with the UUID so that themessage is delivered in a second hop. In this manner, the client neednot be concerned with the DC affinity of the web-socket.

A seventh feature provides an ability to act as a durable messageprovider by which no messages are lost. This feature further provides anability to cache events in case a client is temporarily absent,providing a fire and forget service for microservices. This is achievedby caching undeliverable events for a configurable amount of time aftera web-socket disconnects. On reconnection, the client will present, viaa web-socket message, an identifier that maps it to the previously usedUUID, and the notification service will then deliver all cached messagesbefore continuing with normal message delivery.

An eighth feature provides a client side home pool, which allows clientsto receive events more quickly by directing them to a more efficientpool. The efficiency is improved through locality, speedier delivery ofevents for co-located microservices, and Kafka, together with vendorgear for a particular user.

A ninth feature provides a common utility framework to notify any clientindependent of any type of microservices (i.e., a sender of an event).The common utility framework manages the client notification channel andis a common utility for services, thus abstracting them from thedelivery details.

A tenth feature provides client session management via terminationlifecycle events, which are being sent to all microservices. An eleventhfeature provides abstracting of the Kafka resiliency architecture (e.g.,dual DC or standby DC) via a mere web-socket delivery.

Taken together, these features provide additional advantages, includingthe following: First, ribbon clients were preferred not to talk to Kafkabecause it would require a partition for each user, but an excessivenumber of partitions would not be supported by Kafka, because of a lackof scalability, or else users would receive events that were intendedfor other users Second, web-sockets are used for low latency, but thepresent embodiment uses a common web-socket towards a client, and routesall events from various microservices on the same channel.

There are many scenarios where a client sends requests to a single IPAddress repeatedly even though the services are down. This could be dueto local DNS resolution caching, and could also be due to delays causedby the time taken for GLBs to detect the services being down.

The latencies in the above-described scenario disrupt telephonycommunications due to the nature of real time low latency communication.Despite providing resiliency for multipool/multi-data centermicroservices, clients send requests to the services that are down, dueto local DNS resolution caches, for 20 minutes or more, depending on theoperating system and browser settings.

Resiliency Pattern Seamless resiliency of stateful, low latencytelephony client across multiple Data Centers: Having cloud systemsrunning on multiple Availability Zones (AZ) Data Centers (DC) providesboth the ability to scale and provides resiliency in the event offailure of an AZ and the catastrophic failure of a DC. This comes at theprice of complexity, especially in the interface between cloud andnon-cloud resources where the external resource does not produce areliable stream of events or is only available in one Data Center at anytime. There is complexity in achieving a low latency and seamlessfailover without any event loss that is necessary for mission criticalreal time systems.

In an exemplary embodiment, a solution is provided for the problem oflosing a service that is only available in one DC by having multiple AZsworking against the same DC, through: 1) increasing resiliency for aresource that is available only in one DC by increasing Availabilityzones (i.e., Concurrent monitoring, Deduplication of events fordownstream applications) but also achieve local resiliency between AZ'sat the same time; and 2) when a resource independently decides to movefrom one DC to another DC.

Resiliency when depending on an external Resource available in only oneof multiple Data Centers: A resource R that is external to the cloud maymove between DCs, thereby causing it to no longer be available at theoriginal DC to Service S that acts as a Cloud proxy to R. Service Ssubscribes to an “event source,” which may be R itself or via a proxythat represents R.

FIG. 8 is a flowchart 800 of a method for providing resiliency in atelephony communication system, according to an exemplary embodiment.

Referring to FIG. 8, in an exemplary embodiment, one objective is toprevent loss of service at a client C using service S when resource Rbecomes unavailable in an AZ or DC. In the following example, ResourceR:3 will move from DC:4 to DC:1. 1) In each DC, when service S starts,it obtains, by some means, all the resources R(1:n) that are potentiallyavailable in the local DC (operation S802). 2) In each DC, Service Sattempts to subscribe to an event source for every resource found in theprevious step in at least one AZ within the DC. If the resource isunavailable then Service S produces a message indicating thisinformation. For example, ResourceDiscoveryUpdated {resource=R:3, DC 4,AZ:4b, status:OUT_OF_SERVICE, time t1}. 3) A Client Discovery Service(CDS) consumes these messages and updates its replicated database withthis information so that the status of the resource in all DC's and AZ'sis recorded. 4) Resource R:3 becomes available in DC:4 and Service Sproduces this information to its message bus. For example,ResourceDiscoveryUpdated{resource=R:3, DC:4, AZ:4b, status:IN_SERVICE,time:t2}. 5) Sometime later, a Client wishes to subscribe to Service Sto use resource R3. Client queries CDS to get a list of URLs to accessthe resource (operation S804). 6) CDS queries its database and creates alist of DCs, where each DC has a list of URLs to each AZ that canprovide the service (operation S806) In this case, R3 is only availablein one DC, which has one or more AZ's.

7) Client subscribes to Service S at the first URL in the list. 8)Sometime later, client is using Service S via the URL provided in theprevious step when the Resource independently moves from DC:4 to DC:1.9) Service S in DC-4 detects that the Resource is no longer availableand produces ResourceDiscoveryUpdated (resource=R3, DC=4, AZ=4b,status:=OUT_OF_SERVICE, time=t3) for consumption by both the local CDSand also produces a Subscribe message requesting its peers in other DCsto attempting to re-subscribe, e.g., Subscribe(resource=R3) (operationS808). It may also send a message to the client advising that theservice is temporarily unavailable (operation S808). The client maydisplay this information immediately or after some time if service hasnot been restored. 10) Service Sin each DC processes the Subscriberequest and produces its Update status. It may need to retry for aconfigurable period of time if unable to subscribe when the Resource isnot there. Service S in DC-1 produces ResourceDiscoveryUpdated(resource=R3, DC=1, AZ=1a, status=IN_SERVICE, time=t3). Service S mayalso send a message to the client requesting that it query CDS to get anupdated list of URLs Note: If Service S was able to subscribe in DC-1via a non-cloud proxy, then it will receive the event and produceResourceDiscoveryUpdate (resource=R3, DC=1, AZ=1a, status=IN_SERVICE,time=t3) without needing a Subscribe request from another DC to triggerrecovery (operation S810). 11) CDS processes allResourceDiscoveryUpdated messages and updates its database with the newstatus. 12) CDS produces a ResourceDiscoveryUpdated (resource=R3, DC=1,AZ=1a, status=IN_SERVICE, time=t3) message to all DCs that currentlyshow the resource as out of service (OOS). 13) Service S in DC-1consumes the message indicating the resource is available at another DCand sends a message to the client requesting it to query CDS for anupdated list of URLs (operation S812). 14) Client receives the request,queries CDS and subscribes at the new URL to an AZ in DC-1.

Variant 1: In step 2, if multiple AZ's are available but load-balancingis required, only one AZ may subscribe to the resource. Additionally, ifmultiple AZ's are available but load-balancing and high-availability isrequired, then two or more AZ's subscribe to the resource in order toreach the required level of redundancy. In both cases, theResourceDiscoveryUpdate may include an additional field “weighting” toindicate a preference for the AZ at which the service is available.

Another variant is when the service is available from multiple AZ's,only one “preferred” AZ produces the ResourceDiscoveryUpdate message.When CDS is later queried for a list of AZ's within a DC, it providesthe “preferred” AZ first in the list, but also supplies other AZ's thatit knows can act as backup AZ(s).

Variant 2. If the client discovers that service is no longer availablebefore it receives the message in step 9, it may continuously poll CDSfor status changes.

Variant 3: When service S receives a request to perform an action on aresource that is unavailable, it can self-heal by using CDS to connectto the resource in a remote DC.

FIG. 9 is a flowchart 900 of a method for providing load-balancing for aservice in a telephony communication system, according to an exemplaryembodiment.

Resiliency and load-balancing for Service on multiple AZ's within a DataCenter with dependencies on an external Resource [Note: This describesCTI on two GAIA pools and how DNs are monitored from different pools]:Referring to FIG. 9, a service that needs to achieve load-balancing ofits subscriptions to many Resources may divide the set of Resourcesbetween each of the AZ's (operation S902). For example, if each Resourcehas a unique identifier, then the division could be determined bygetting (a) the hash of the Resource-ID and (b) a modulus of the resultof (a) with the number of AZ's.

A service that needs to be resilient must subscribe for the sameResource using more than one AZ within the same DC in case an AZ becomesunavailable. However, the introduction of a redundant instance of theservice in multiple AZ's subscribed to the same resource must not causethe client to receive duplicate events.

In an exemplary embodiment, a mechanism for a service to be bothresilient and achieve load-balancing is provided:

TABLE 1 Topics with levels of resiliency Partition Resiliency TopicAssignor Index Redundancy Level external-request Assignor-0 0 (none)internal-redundant-1 Assignor-1 1 internal-redundant-2 Assignor-2 2

Topic “external-request” is the external-facing topic used by clients tosend requests to the service. Its partitions are allocated using“Assignor-O”.

Topic “internal-redundant-1” is a topic used for internal communicationbetween instances of the service in order to control which instances areresponsible for subscribing to subsets of resources as the first tier ofredundancy. Its partitions are allocated using “Assignor-1”.

Topic “internal-redundant-2” is similar to topic “internal-redundant-1”but is the optional second tier of redundancy. The maximum level ofredundancy is one less than the total number of availability zones. Itspartitions are allocated using “Assignor-2”.

All topics have the same number of partitions. All instances of theService subscribe to these topics using the same “consumer-group,” sothat the message bus will load-balance messages among each member,according to the Consumer's choice of partition assignor. Each partitionassignor uses the following deterministic algorithm to assignpartitions: Partition ‘p’ maps to AZ indices according to functionmodulo ((p+a)/Z)=z where “p” is the partition number, “a” is theassignor index, Z is the total number of Availability Zones, modulo is astandard modulo function (i.e., returns the remainder of a division),and “z” is the zone index. The result is illustrated in an example inTable I for a topic with 13 partitions over 4 AZ's.

TABLE 2 Assignment of partitions to Availability Zones using modulo((p + a)/Z) resulting in no partition being assigned more than once tothe same AZ Availability Zone AZ- AZ- AZ- AZ- index: 0 index: 1 index: 2index: 3 Assignor-index: 0 0, 4, 8, 12 1, 5, 9 2, 6, 10 3, 7, 11Assignor-index: 1 3, 7, 11 0, 4, 8, 12 1, 5, 9 2, 6, 10 Assignor-index:2 2, 6, 10 3, 7, 11 0, 4, 8, 12 1, 5, 9

TABLE 3 assignment of partitions to Availability Zones when AZ-1 isunavailable Availability Zone AZ- AZ- AZ- AZ- index: 0 index: 1 index: 2index: 3 Assignor-index: 0 0, 4, 8, 12, 9 1, 5, 9 2, 6, 100, 1 3, 7, 11,5 Assignor-index: 1 3, 7, 11, 8 0, 4, 8, 12 1, 5, 9, 0, 12 2, 6, 10, 4Assignor-index: 2 2, 6, 10, 11 3, 7, 11 0, 4, 8, 12, 3 1, 5, 9, 7

As is evident from Table 3, when one or more AZ's are not available, theinitial calculation for the assignment of partitions does not change.Consequently, partitions are allocated to the same AZ's regardless ofthe availability of other AZs (i.e., sticky assignment). The partitionsthat used to be assigned to missing AZs are allocated by any algorithmthat evenly distributes them among surviving AZ's (operation S904).

The effect of configuring topics and partition assignors in this way isto guarantee that 1) Partitions are evenly spread across AZ's in amanner that is sticky so that if an AZ is lost, the resultingre-assignment of partitions is minimized; and 2) any given partitionindex allocated by Assignor-0 is also allocated to different AZ's bybackup assignors. For example, Partition 0 is allocated to AZ-0 byAssignor-0 and to AZ-2 by Assignor-2.

1) On startup, the application will consume from the external facing“external-request” topic and all “internal-redundant” topics using thesame “consumer-group”. 2) On startup, the same or different applicationwill query the total set of resources and Produce one ResourceAssignedmessage per Resource using the unique Resource-ID as Kafka routing keyto the external facing “request” topic. 3) On consuming aResourceAssigned message from the external facing “request” topic, 3a)subscribe to the event source for the specified Resource (operationS906); 3b) produce the same subscription message to remote AZ topic(s)(operation S908), and 3c) persist the Primary mapping of resource-id to“request” topic partition index (operation S910).

4) On consuming a subscription message from the application's internal“local AZ” topic, 4a) subscribe to the event source for the specifiedresource-id (operation S912), and 4b) persist the Backup mapping ofresource-id to “local AZ” topic partition index (operation S914). 5) Onconsuming a request from the external facing “request” topic, theapplication will process the request by propagating the request to theevent source 6) On receiving an event from the event source, 6a) theprimary caches the message containing details of the event withrole:primary and produces it to the output topic, and 6b) the backup(s)produces an equivalent message but to the input “request” topic withmetadata role:backup.

7) On consuming a message from the external facing “request” topic withmetadata role:backup, the primary instance for the routing key uses itscache to validate that it has already produced the equivalent messageand if so, deletes the message from the cache. If validation fails andconnectivity to the event source is known to be lost, then the messageis propagated to the output topic. Otherwise the message is cached andthe key is added to a list of keys requiring audit. 8) One or morethreads are dedicated to audit out-of-sync keys. On finding a key thathas a cached message from a backup source but no messages from theprimary, then if the backup message is older than t msec, 8a) the backupmessage is produced to the “output” topic with metadata role:backup anddeleted, and 8b) the primary event source is marked as “down” so thatthe next messages from the backup will be propagated immediately to theoutput topic.

A variant of steps 7 and 8, i.e., Deduping functionality, can be done bya dedicated microservice.

FIG. 10 is a flowchart 1000 of a method for providing resiliency withrespect to a potential loss of a cluster of an Kafka stream processingplatform, according to an exemplary embodiment.

Resiliency for transient or permanent loss of Kafka nodes/cluster:Referring to FIG. 10, although Kafka clusters are resilient to the lossof any one node, there are a number of ways in which an application mayfail to produce a message to the cluster. For example, the producer'smetadata may be stale, thereby causing it to produce a message to thewrong node (i.e., incorrect PartitionLeader). Rather than wait forseveral seconds until the system recovers, an exemplary embodimentallows the message to be propagated to consumers with minimal delay.

1) Topic is configured on both the primary and backup Kafka cluster(operation S1002). 2) Consumers always actively consume from bothcluster topics. 3) Producer is configured to first attempt to produce tothe primary with a short fail-to-send timeout (operation S1004). 4) Ifthe message fails to be produced within the “failed-to-send” timeout, anattempt is made to produce to the fallback topic on the fallback cluster(operation S1006).

Variant 1: For this variant, it is assumed that 1) only one of the manypartitions of the topic may be affected by a delay at the broker, and 2)an attempt to produce a message to this partition often delays theclient thread (buffer full or metadata not available). In this variant,delays are avoided in sending messages to other partitions that are notaffected by the issue by delegating the send to a “sequential-executor”using the target partition as the execution key. This has the effect ofqueuing messages bound for the same partition, whereas messages boundfor other partitions are sent without delay.

Variant 2: In order to minimize the number of messages affected by adelay, model the state of the topic+partition as UP or DOWN. Once amessage fails to be produced, mark the topic:partition as DOWN andsubsequent messages are immediately routed to the fallback clusterwithout attempting to send to the primary (operation S1008). Ontransitioning to DOWN, monitor the topic:partition for recovery byquerying for metadata (operation S1010) On successfully retrieving themetadata, model the topic partition as UP (operation S1012).

Variant 3: If it is important to maintain strict ordering of messages,then on recovery of a topic:partition in Variant 2, delay the transferback to the primary cluster so that the consumer will have consumed allmessages from the fallback cluster before receiving messages on theproblem partition via the primary cluster.

Accordingly, with this technology, an optimized process for handlinglarge number of customer service interactions to ensure efficient andaccurate interaction servicing results is provided.

Although the invention has been described with reference to severalexemplary embodiments, it is understood that the words that have beenused are words of description and illustration, rather than words oflimitation. Changes may be made within the purview of the appendedclaims, as presently stated and as amended, without departing from thescope and spirit of the present disclosure in its aspects. Although theinvention has been described with reference to particular means,materials and embodiments, the invention is not intended to be limitedto the particulars disclosed: rather the invention extends to allfunctionally equivalent structures, methods, and uses such as are withinthe scope of the appended claims.

For example, while the computer-readable medium may be described as asingle medium, the term “computer-readable medium” includes a singlemedium or multiple media, such as a centralized or distributed database,and/or associated caches and servers that store one or more sets ofinstructions. The term “computer-readable medium” shall also include anymedium that is capable of storing, encoding or carrying a set ofinstructions for execution by a processor or that cause a computersystem to perform any one or more of the embodiments disclosed herein.

The computer-readable medium may comprise a non-transitorycomputer-readable medium or media and/or comprise a transitorycomputer-readable medium or media. In a particular non-limiting,exemplary embodiment, the computer-readable medium can include asolid-state memory such as a memory card or other package that housesone or more non-volatile read-only memories. Further, thecomputer-readable medium can be a random-access memory or other volatilere-writable memory. Additionally, the computer-readable medium caninclude a magneto-optical or optical medium, such as a disk or tapes orother storage device to capture carrier wave signals such as a signalcommunicated over a transmission medium. Accordingly, the disclosure isconsidered to include any computer-readable medium or other equivalentsand successor media, in which data or instructions may be stored.

Although the present application describes specific embodiments whichmay be implemented as computer programs or code segments incomputer-readable media, it is to be understood that dedicated hardwareimplementations, such as application specific integrated circuits,programmable logic arrays and other hardware devices, can be constructedto implement one or more of the embodiments described hereinApplications that may include the various embodiments set forth hereinmay broadly include a variety of electronic and computer systems.Accordingly, the present application may encompass software, firmware,and hardware implementations, or combinations thereof. Nothing in thepresent application should be interpreted as being implemented orimplementable solely with software and not hardware.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the disclosure is not limited tosuch standards and protocols. Such standards are periodically supersededby faster or more efficient equivalents having essentially the samefunctions. Accordingly, replacement standards and protocols having thesame or similar functions are considered equivalents thereof.

The illustrations of the embodiments described herein are intended toprovide a general understanding of the various embodiments. Theillustrations are not intended to serve as a complete description of allthe elements and features of apparatus and systems that utilize thestructures or methods described herein Many other embodiments may beapparent to those of skill in the art upon reviewing the disclosure.Other embodiments may be utilized and derived from the disclosure, suchthat structural and logical substitutions and changes may be madewithout departing from the scope of the disclosure. Additionally, theillustrations are merely representational and may not be drawn to scale.Certain proportions within the illustrations may be exaggerated, whileother proportions may be minimized. Accordingly, the disclosure and thefigures are to be regarded as illustrative rather than restrictive.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is submitted with the understanding thatit will not be used to interpret or limit the scope or meaning of theclaims. In addition, in the foregoing Detailed Description, variousfeatures may be grouped together or described in a single embodiment forthe purpose of streamlining the disclosure. This disclosure is not to beinterpreted as reflecting an intention that the claimed embodimentsrequire more features than are expressly recited in each claim. Rather,as the following claims reflect, inventive subject matter may bedirected to less than all of the features of any of the disclosedembodiments. Thus, the following claims are incorporated into theDetailed Description, with each claim standing on its own as definingseparately claimed subject matter.

The above disclosed subject matter is to be considered illustrative, andnot restrictive, and the appended claims are intended to cover all suchmodifications, enhancements, and other embodiments which fall within thetrue spirit and scope of the present disclosure. Thus, to the maximumextent allowed by law, the scope of the present disclosure is to bedetermined by the broadest permissible interpretation of the followingclaims, and their equivalents, and shall not be restricted or limited bythe foregoing detailed description.

What is claimed is:
 1. A method for providing resiliency in a telephonycommunication system, the method being implemented by at least oneprocessor, the method comprising: obtaining, by the at least oneprocessor, a plurality of resources that are available in a first datacenter; receiving, by the at least one processor from a client, arequest for accessing a first resource from among the plurality ofresources; transmitting, by the at least one processor to the client, afirst Uniform Resource Locator (URL) that includes information forfacilitating a client access to the first resource in the first datacenter; when the first resource becomes unavailable in the first datacenter and available in a second data center, transmitting, by the atleast one processor to the second data center, a subscribe message forfacilitating a client access to the first resource in the second datacenter; and when the client access to the first resource becomesavailable in at least one from among the first data center and thesecond data center, transmitting, by the at least one processor to theclient, a second URL that includes information for facilitating theclient access to the first resource in the available at least one fromamong the first data center and the second data center.
 2. The method ofclaim 1, further comprising: when the first resource becomes unavailablein the first data center, transmitting, to a client discovery service, astatus message that includes an identification of the first resource, anidentification of the first data center, an identification of anavailability zone within the first data center at which the firstresource was previously available, an out-of-service status, and acurrent time.
 3. The method of claim 1, further comprising: when thefirst resource becomes unavailable in the first data center,transmitting, to the client, a message indicating that the firstresource is temporarily unavailable.
 4. The method of claim 1, furthercomprising: when the first resource becomes available in the second datacenter, transmitting, to a client discovery service, a status messagethat includes an identification of the first resource, an identificationof the second data center, an identification of an availability zonewithin the second data center at which the first resource has becomeavailable, an in-service status, and a current time.